Computational visualization techniques are used to explore, in an immersive fashion, inherent data structure in both an unsupervised and supervised manner. Supervision is provided via i) domain knowledge contained in breast cancer data, and ii) unsupervised data mining procedures, such as k-means and rough set based k-means. Despite no explicit preprocessing, exploration of high dimensional data sets is demonstrated. In particular, some of the visual perspectives presented in this study may be useful for helping to understand breast cancer gene expressions or results from computational data mining procedures.